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University: Georgia Tech

You searched for subject:(NONPARAMETRIC ESTIMATION MATHEMATICAL STATISTICS ). Showing records 1 – 30 of 615 total matches.

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Georgia Tech

1. Gong, Yun. Empirical likelihood and extremes.

Degree: PhD, Mathematics, 2012, Georgia Tech

 In 1988, Owen introduced empirical likelihood as a nonparametric method for constructing confidence intervals and regions. Since then, empirical likelihood has been studied extensively in… (more)

Subjects/Keywords: Diffusion processes; Nonparametric likelihood; GARCH; ROC curve; Value at Risk; Empirical likelihood; Extremal problems (Mathematics); Golden section; Calculus of variations; Bootstrap (Statistics); Mathematical statistics

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APA (6th Edition):

Gong, Y. (2012). Empirical likelihood and extremes. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/43581

Chicago Manual of Style (16th Edition):

Gong, Yun. “Empirical likelihood and extremes.” 2012. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/43581.

MLA Handbook (7th Edition):

Gong, Yun. “Empirical likelihood and extremes.” 2012. Web. 22 Aug 2019.

Vancouver:

Gong Y. Empirical likelihood and extremes. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/43581.

Council of Science Editors:

Gong Y. Empirical likelihood and extremes. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/43581


Georgia Tech

2. Francis, Ollie Brown. Elements of linear regression: an expository development.

Degree: MS, Applied Mathematics, 1960, Georgia Tech

Subjects/Keywords: Mathematical statistics

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APA (6th Edition):

Francis, O. B. (1960). Elements of linear regression: an expository development. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/30385

Chicago Manual of Style (16th Edition):

Francis, Ollie Brown. “Elements of linear regression: an expository development.” 1960. Masters Thesis, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/30385.

MLA Handbook (7th Edition):

Francis, Ollie Brown. “Elements of linear regression: an expository development.” 1960. Web. 22 Aug 2019.

Vancouver:

Francis OB. Elements of linear regression: an expository development. [Internet] [Masters thesis]. Georgia Tech; 1960. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/30385.

Council of Science Editors:

Francis OB. Elements of linear regression: an expository development. [Masters Thesis]. Georgia Tech; 1960. Available from: http://hdl.handle.net/1853/30385


Georgia Tech

3. Zhou, Fan. Statistical inference for high dimensional data with low rank structure.

Degree: PhD, Mathematics, 2018, Georgia Tech

 We study two major topics on statistical inference for high dimensional data with low rank structure occurred in many machine learning and statistics applications. The… (more)

Subjects/Keywords: Nonparametric statistics; Matrix completion; Low rank; Nuclear norm; Tensor; Singular vector perturbation

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APA (6th Edition):

Zhou, F. (2018). Statistical inference for high dimensional data with low rank structure. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60750

Chicago Manual of Style (16th Edition):

Zhou, Fan. “Statistical inference for high dimensional data with low rank structure.” 2018. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/60750.

MLA Handbook (7th Edition):

Zhou, Fan. “Statistical inference for high dimensional data with low rank structure.” 2018. Web. 22 Aug 2019.

Vancouver:

Zhou F. Statistical inference for high dimensional data with low rank structure. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/60750.

Council of Science Editors:

Zhou F. Statistical inference for high dimensional data with low rank structure. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60750

4. Remenyi, Norbert. Contributions to Bayesian wavelet shrinkage.

Degree: PhD, Industrial and Systems Engineering, 2012, Georgia Tech

 This thesis provides contributions to research in Bayesian modeling and shrinkage in the wavelet domain. Wavelets are a powerful tool to describe phenomena rapidly changing… (more)

Subjects/Keywords: Bayes factor; Bayesian estimation; Bayesian infere; Wavelets (Mathematics); Bayesian statistical decision theory; Mathematical statistics

…time, and wavelet-based modeling has become a standard technique in many areas of statistics… …and more broadly, in sciences and engineering. Bayesian modeling and estimation in the… …wavelet domain have found useful applications in nonparametric regression, image denoising, and… …for applications in nonparametric regression, image denoising, and partially linear models… …main focus of the overview chapter is on nonparametric regression, where the observations… 

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APA (6th Edition):

Remenyi, N. (2012). Contributions to Bayesian wavelet shrinkage. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/45898

Chicago Manual of Style (16th Edition):

Remenyi, Norbert. “Contributions to Bayesian wavelet shrinkage.” 2012. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/45898.

MLA Handbook (7th Edition):

Remenyi, Norbert. “Contributions to Bayesian wavelet shrinkage.” 2012. Web. 22 Aug 2019.

Vancouver:

Remenyi N. Contributions to Bayesian wavelet shrinkage. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/45898.

Council of Science Editors:

Remenyi N. Contributions to Bayesian wavelet shrinkage. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/45898


Georgia Tech

5. Jones, Martin Lee. Universal constants in optimal stopping theory.

Degree: PhD, Mathematics, 1989, Georgia Tech

Subjects/Keywords: Probabilities; Optimal stopping (Mathematical statistics)

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APA (6th Edition):

Jones, M. L. (1989). Universal constants in optimal stopping theory. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/30092

Chicago Manual of Style (16th Edition):

Jones, Martin Lee. “Universal constants in optimal stopping theory.” 1989. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/30092.

MLA Handbook (7th Edition):

Jones, Martin Lee. “Universal constants in optimal stopping theory.” 1989. Web. 22 Aug 2019.

Vancouver:

Jones ML. Universal constants in optimal stopping theory. [Internet] [Doctoral dissertation]. Georgia Tech; 1989. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/30092.

Council of Science Editors:

Jones ML. Universal constants in optimal stopping theory. [Doctoral Dissertation]. Georgia Tech; 1989. Available from: http://hdl.handle.net/1853/30092

6. Saeed, Usman. Adaptive numerical techniques for the solution of electromagnetic integral equations.

Degree: PhD, Electrical and Computer Engineering, 2011, Georgia Tech

 Various error estimation and adaptive refinement techniques for the solution of electromagnetic integral equations were developed. Residual based error estimators and h-refinement implementations were done… (more)

Subjects/Keywords: Error estimation; Electromagnetic integral equations; Boundary element method; LCN; Method of moments; Adaptive refinement; Electromagnetic measurements; Electromagnetism Mathematical models; Moments method (Statistics); Numerical grid generation (Numerical analysis)

…problem in Figure 3 computed using different error estimation schemes. 57 Figure 4.5: Global… …estimation techniques for the numerical solution of differential equations using finite element… …computationally inexpensive as desired. This dissertation investigates several novel error estimation… …approach, we present various explicit error estimation techniques and use them to carry out… …based explicit error estimation techniques for the MoM solution of electromagnetic integral… 

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APA (6th Edition):

Saeed, U. (2011). Adaptive numerical techniques for the solution of electromagnetic integral equations. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/41173

Chicago Manual of Style (16th Edition):

Saeed, Usman. “Adaptive numerical techniques for the solution of electromagnetic integral equations.” 2011. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/41173.

MLA Handbook (7th Edition):

Saeed, Usman. “Adaptive numerical techniques for the solution of electromagnetic integral equations.” 2011. Web. 22 Aug 2019.

Vancouver:

Saeed U. Adaptive numerical techniques for the solution of electromagnetic integral equations. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/41173.

Council of Science Editors:

Saeed U. Adaptive numerical techniques for the solution of electromagnetic integral equations. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/41173


Georgia Tech

7. Roberts, Craig Arnold. Modeling the relationships between microscopic and macroscopic travel activity on freeways : bridging the gap between current travel demand models and emerging mobile emission models.

Degree: PhD, Civil and environmental engineering, 1999, Georgia Tech

Subjects/Keywords: Traffic estimation Mathematical models; Transportation Planning; Automobiles Motors

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APA (6th Edition):

Roberts, C. A. (1999). Modeling the relationships between microscopic and macroscopic travel activity on freeways : bridging the gap between current travel demand models and emerging mobile emission models. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/32873

Chicago Manual of Style (16th Edition):

Roberts, Craig Arnold. “Modeling the relationships between microscopic and macroscopic travel activity on freeways : bridging the gap between current travel demand models and emerging mobile emission models.” 1999. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/32873.

MLA Handbook (7th Edition):

Roberts, Craig Arnold. “Modeling the relationships between microscopic and macroscopic travel activity on freeways : bridging the gap between current travel demand models and emerging mobile emission models.” 1999. Web. 22 Aug 2019.

Vancouver:

Roberts CA. Modeling the relationships between microscopic and macroscopic travel activity on freeways : bridging the gap between current travel demand models and emerging mobile emission models. [Internet] [Doctoral dissertation]. Georgia Tech; 1999. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/32873.

Council of Science Editors:

Roberts CA. Modeling the relationships between microscopic and macroscopic travel activity on freeways : bridging the gap between current travel demand models and emerging mobile emission models. [Doctoral Dissertation]. Georgia Tech; 1999. Available from: http://hdl.handle.net/1853/32873


Georgia Tech

8. Tan, Matthias H. Y. Contributions to quality improvement methodologies and computer experiments.

Degree: PhD, Industrial and Systems Engineering, 2013, Georgia Tech

 This dissertation presents novel methodologies for five problem areas in modern quality improvement and computer experiments, i.e., selective assembly, robust design with computer experiments, multivariate… (more)

Subjects/Keywords: Selective assembly; Robust parameter design; Quadratic loss; Multivariate quality control; Mean shift identification; Split plot experiments; Bayesian model selection; Space-filling designs; Minimax designs; Sampling (Statistics); Mathematical statistics; Quality control

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APA (6th Edition):

Tan, M. H. Y. (2013). Contributions to quality improvement methodologies and computer experiments. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/48936

Chicago Manual of Style (16th Edition):

Tan, Matthias H Y. “Contributions to quality improvement methodologies and computer experiments.” 2013. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/48936.

MLA Handbook (7th Edition):

Tan, Matthias H Y. “Contributions to quality improvement methodologies and computer experiments.” 2013. Web. 22 Aug 2019.

Vancouver:

Tan MHY. Contributions to quality improvement methodologies and computer experiments. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/48936.

Council of Science Editors:

Tan MHY. Contributions to quality improvement methodologies and computer experiments. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/48936


Georgia Tech

9. Kim, Heeyoung. Statistical methods for function estimation and classification.

Degree: PhD, Industrial and Systems Engineering, 2011, Georgia Tech

 This thesis consists of three chapters. The first chapter focuses on adaptive smoothing splines for fitting functions with varying roughness. In the first part of… (more)

Subjects/Keywords: Adaptive smoothing splines; Asymptotic optimality; Coordinate measuring machine; Wavelets; Classification; Mathematical statistics; Spline theory; Function spaces

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APA (6th Edition):

Kim, H. (2011). Statistical methods for function estimation and classification. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44806

Chicago Manual of Style (16th Edition):

Kim, Heeyoung. “Statistical methods for function estimation and classification.” 2011. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/44806.

MLA Handbook (7th Edition):

Kim, Heeyoung. “Statistical methods for function estimation and classification.” 2011. Web. 22 Aug 2019.

Vancouver:

Kim H. Statistical methods for function estimation and classification. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/44806.

Council of Science Editors:

Kim H. Statistical methods for function estimation and classification. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/44806


Georgia Tech

10. Morgan, Frank Harrold. The correspondence theorem.

Degree: MS, Applied Mathematics, 1964, Georgia Tech

Subjects/Keywords: Distribution (Probability theory); Intergrals, Generalized; Mathematical statistics

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APA (6th Edition):

Morgan, F. H. (1964). The correspondence theorem. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/28845

Chicago Manual of Style (16th Edition):

Morgan, Frank Harrold. “The correspondence theorem.” 1964. Masters Thesis, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/28845.

MLA Handbook (7th Edition):

Morgan, Frank Harrold. “The correspondence theorem.” 1964. Web. 22 Aug 2019.

Vancouver:

Morgan FH. The correspondence theorem. [Internet] [Masters thesis]. Georgia Tech; 1964. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/28845.

Council of Science Editors:

Morgan FH. The correspondence theorem. [Masters Thesis]. Georgia Tech; 1964. Available from: http://hdl.handle.net/1853/28845


Georgia Tech

11. Shieh, Jung-Sheng. Some applications of the Bechhofer-Kiefer-Sobel generalized sequential probability ratio test to software reliability testing.

Degree: PhD, Mathematics, 1992, Georgia Tech

Subjects/Keywords: Computer software Reliability; Sequential analysis; Mathematical statistics

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APA (6th Edition):

Shieh, J. (1992). Some applications of the Bechhofer-Kiefer-Sobel generalized sequential probability ratio test to software reliability testing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/28928

Chicago Manual of Style (16th Edition):

Shieh, Jung-Sheng. “Some applications of the Bechhofer-Kiefer-Sobel generalized sequential probability ratio test to software reliability testing.” 1992. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/28928.

MLA Handbook (7th Edition):

Shieh, Jung-Sheng. “Some applications of the Bechhofer-Kiefer-Sobel generalized sequential probability ratio test to software reliability testing.” 1992. Web. 22 Aug 2019.

Vancouver:

Shieh J. Some applications of the Bechhofer-Kiefer-Sobel generalized sequential probability ratio test to software reliability testing. [Internet] [Doctoral dissertation]. Georgia Tech; 1992. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/28928.

Council of Science Editors:

Shieh J. Some applications of the Bechhofer-Kiefer-Sobel generalized sequential probability ratio test to software reliability testing. [Doctoral Dissertation]. Georgia Tech; 1992. Available from: http://hdl.handle.net/1853/28928


Georgia Tech

12. Brubaker, S. Charles. Extensions of principal components analysis.

Degree: PhD, Computing, 2009, Georgia Tech

 Principal Components Analysis is a standard tool in data analysis, widely used in data-rich fields such as computer vision, data mining, bioinformatics, and econometrics. For… (more)

Subjects/Keywords: Principal components analysis; Planted cliques; Random tensors; Mixture models; Principal components analysis; Algorithms; Mathematical statistics; Eigenvectors

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APA (6th Edition):

Brubaker, S. C. (2009). Extensions of principal components analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/29645

Chicago Manual of Style (16th Edition):

Brubaker, S Charles. “Extensions of principal components analysis.” 2009. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/29645.

MLA Handbook (7th Edition):

Brubaker, S Charles. “Extensions of principal components analysis.” 2009. Web. 22 Aug 2019.

Vancouver:

Brubaker SC. Extensions of principal components analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2009. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/29645.

Council of Science Editors:

Brubaker SC. Extensions of principal components analysis. [Doctoral Dissertation]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/29645


Georgia Tech

13. Friedman, David J. Evaluation of predictive equations using biased estimators for the linear regression model.

Degree: PhD, Industrial engineering, 1983, Georgia Tech

Subjects/Keywords: Regression analysis; Log-linear models; Mathematical statistics

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APA (6th Edition):

Friedman, D. J. (1983). Evaluation of predictive equations using biased estimators for the linear regression model. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/33440

Chicago Manual of Style (16th Edition):

Friedman, David J. “Evaluation of predictive equations using biased estimators for the linear regression model.” 1983. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/33440.

MLA Handbook (7th Edition):

Friedman, David J. “Evaluation of predictive equations using biased estimators for the linear regression model.” 1983. Web. 22 Aug 2019.

Vancouver:

Friedman DJ. Evaluation of predictive equations using biased estimators for the linear regression model. [Internet] [Doctoral dissertation]. Georgia Tech; 1983. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/33440.

Council of Science Editors:

Friedman DJ. Evaluation of predictive equations using biased estimators for the linear regression model. [Doctoral Dissertation]. Georgia Tech; 1983. Available from: http://hdl.handle.net/1853/33440


Georgia Tech

14. Smith, Andrew Korb. New results in dimension reduction and model selection.

Degree: PhD, Industrial and Systems Engineering, 2008, Georgia Tech

 Dimension reduction is a vital tool in many areas of applied statistics in which the dimensionality of the predictors can be large. In such cases,… (more)

Subjects/Keywords: Hlle; Ltsa; Manifold learning; Model selection criteria; Mathematical models; Mathematical statistics; Correlation (Statistics); Algorithms

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APA (6th Edition):

Smith, A. K. (2008). New results in dimension reduction and model selection. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/22586

Chicago Manual of Style (16th Edition):

Smith, Andrew Korb. “New results in dimension reduction and model selection.” 2008. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/22586.

MLA Handbook (7th Edition):

Smith, Andrew Korb. “New results in dimension reduction and model selection.” 2008. Web. 22 Aug 2019.

Vancouver:

Smith AK. New results in dimension reduction and model selection. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/22586.

Council of Science Editors:

Smith AK. New results in dimension reduction and model selection. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/22586


Georgia Tech

15. Chou, I-Chun. Parameter estimation and network identification in metabolic pathway systems.

Degree: PhD, Biomedical Engineering, 2008, Georgia Tech

 Cells are able to function and survive due to a delicate orchestration of the expression of genes and their downstream products at the genetic, transcriptomic,… (more)

Subjects/Keywords: Metabolic network; Biochemical systems theory; Network identification; Parameter estimation; Metabolism; Mathematical models; Algorithms

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APA (6th Edition):

Chou, I. (2008). Parameter estimation and network identification in metabolic pathway systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/26513

Chicago Manual of Style (16th Edition):

Chou, I-Chun. “Parameter estimation and network identification in metabolic pathway systems.” 2008. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/26513.

MLA Handbook (7th Edition):

Chou, I-Chun. “Parameter estimation and network identification in metabolic pathway systems.” 2008. Web. 22 Aug 2019.

Vancouver:

Chou I. Parameter estimation and network identification in metabolic pathway systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/26513.

Council of Science Editors:

Chou I. Parameter estimation and network identification in metabolic pathway systems. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/26513


Georgia Tech

16. Wang, Shuchun. Exponential Smoothing for Forecasting and Bayesian Validation of Computer Models.

Degree: PhD, Industrial and Systems Engineering, 2006, Georgia Tech

 Despite their success and widespread usage in industry and business, ES methods have received little attention from the statistical community. We investigate three types of… (more)

Subjects/Keywords: State space model; Prediction intervals; ARIMA models; Model selection; Maximum likelihood estimation; Gaussian process; Smoothing (Statistics); Computer simulation

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APA (6th Edition):

Wang, S. (2006). Exponential Smoothing for Forecasting and Bayesian Validation of Computer Models. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/19753

Chicago Manual of Style (16th Edition):

Wang, Shuchun. “Exponential Smoothing for Forecasting and Bayesian Validation of Computer Models.” 2006. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/19753.

MLA Handbook (7th Edition):

Wang, Shuchun. “Exponential Smoothing for Forecasting and Bayesian Validation of Computer Models.” 2006. Web. 22 Aug 2019.

Vancouver:

Wang S. Exponential Smoothing for Forecasting and Bayesian Validation of Computer Models. [Internet] [Doctoral dissertation]. Georgia Tech; 2006. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/19753.

Council of Science Editors:

Wang S. Exponential Smoothing for Forecasting and Bayesian Validation of Computer Models. [Doctoral Dissertation]. Georgia Tech; 2006. Available from: http://hdl.handle.net/1853/19753

17. Valencia Arboleda, Carlos Felipe. Contributions to statistical learning and its applications in personalized medicine.

Degree: PhD, Industrial and Systems Engineering, 2013, Georgia Tech

 This dissertation, in general, is about finding stable solutions to statistical models with very large number of parameters and to analyze their asymptotic statistical properties.… (more)

Subjects/Keywords: Statistical learning; Regularization; Penalized estimation; Individualized treatment rule; Statistics; Multivariate analysis; Regression analysis

nonparametric estimation of f0 . The particular interest in this project is to analysis the… …LIST OF FIGURES 1 Estimation errors in logarithmic scale… …18 3 Estimation and Prediction errors in logarithmic scale when the eigenvalues in the… …smoothness is assumed in the case of non-parametric function estimation, or sparsity in the case of… …methods based on penalized estimation. Those procedures find an estimator that is the result of… 

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APA (6th Edition):

Valencia Arboleda, C. F. (2013). Contributions to statistical learning and its applications in personalized medicine. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49143

Chicago Manual of Style (16th Edition):

Valencia Arboleda, Carlos Felipe. “Contributions to statistical learning and its applications in personalized medicine.” 2013. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/49143.

MLA Handbook (7th Edition):

Valencia Arboleda, Carlos Felipe. “Contributions to statistical learning and its applications in personalized medicine.” 2013. Web. 22 Aug 2019.

Vancouver:

Valencia Arboleda CF. Contributions to statistical learning and its applications in personalized medicine. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/49143.

Council of Science Editors:

Valencia Arboleda CF. Contributions to statistical learning and its applications in personalized medicine. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/49143

18. Parker, Lonnie Thomas. Science-centric sampling approaches of geo-physical environments for realistic robot navigation.

Degree: PhD, Electrical and Computer Engineering, 2012, Georgia Tech

 The objective of this research effort is to provide a methodology for assessing the effectiveness of sampling techniques used to gather different types of geo-physical… (more)

Subjects/Keywords: Sampling strategies; Navigation; Robotic surveying; Spatial estimation; Mobile robots; Sampling (Statistics); Artificial intelligence Geophysical applications; Navigation

…Comparing expected and actual error between traditional and informed estimation methods, M N = 9… …31 Comparing expected and actual error between informed and traditional estimation methods… …our informed estimation methodology. Navigation is in the positive x direction for… …informed estimation using lawnmower-traditional navigation as a sampling scheme as applied to… …Performance of informed estimation using lawnmower-random navigation as a sampling scheme as applied… 

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APA (6th Edition):

Parker, L. T. (2012). Science-centric sampling approaches of geo-physical environments for realistic robot navigation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44813

Chicago Manual of Style (16th Edition):

Parker, Lonnie Thomas. “Science-centric sampling approaches of geo-physical environments for realistic robot navigation.” 2012. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/44813.

MLA Handbook (7th Edition):

Parker, Lonnie Thomas. “Science-centric sampling approaches of geo-physical environments for realistic robot navigation.” 2012. Web. 22 Aug 2019.

Vancouver:

Parker LT. Science-centric sampling approaches of geo-physical environments for realistic robot navigation. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/44813.

Council of Science Editors:

Parker LT. Science-centric sampling approaches of geo-physical environments for realistic robot navigation. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44813

19. Minsker, Stanislav. Non-asymptotic bounds for prediction problems and density estimation.

Degree: PhD, Mathematics, 2012, Georgia Tech

 This dissertation investigates the learning scenarios where a high-dimensional parameter has to be estimated from a given sample of fixed size, often smaller than the… (more)

Subjects/Keywords: Active learning; Sparse recovery; Oracle inequality; Confidence bands; Infinite dictionary; Estimation theory Asymptotic theory; Estimation theory; Distribution (Probability theory); Prediction theory; Active learning; Algorithms; Mathematical optimization; Chebyshev approximation

…researcher. In general, consistent estimation of all parameters of the system is impossible in this… …nonparametric assumptions on the regression function – namely, we assume that it belongs to a certain… …estimation of regression function in sup-norm is sensitive to the geometry of design distribution… …mainly because the quality of estimation depends on the local amount of data at every point… …adaptive confidence bands for the regression function. 17 Nonparametric confidence bands form… 

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APA (6th Edition):

Minsker, S. (2012). Non-asymptotic bounds for prediction problems and density estimation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44808

Chicago Manual of Style (16th Edition):

Minsker, Stanislav. “Non-asymptotic bounds for prediction problems and density estimation.” 2012. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/44808.

MLA Handbook (7th Edition):

Minsker, Stanislav. “Non-asymptotic bounds for prediction problems and density estimation.” 2012. Web. 22 Aug 2019.

Vancouver:

Minsker S. Non-asymptotic bounds for prediction problems and density estimation. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/44808.

Council of Science Editors:

Minsker S. Non-asymptotic bounds for prediction problems and density estimation. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44808


Georgia Tech

20. Young, Stephen J. Random dot product graphs: a flexible model for complex networks.

Degree: PhD, Mathematics, 2008, Georgia Tech

 Over the last twenty years, as biological, technological, and social net- works have risen in prominence and importance, the study of complex networks has attracted… (more)

Subjects/Keywords: Comlex networks; Random graphs; Power-law; Clustering; Assortativity; Spectral gap; Conductance; Cluster analysis; Mathematical statistics; Random graphs

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APA (6th Edition):

Young, S. J. (2008). Random dot product graphs: a flexible model for complex networks. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/26548

Chicago Manual of Style (16th Edition):

Young, Stephen J. “Random dot product graphs: a flexible model for complex networks.” 2008. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/26548.

MLA Handbook (7th Edition):

Young, Stephen J. “Random dot product graphs: a flexible model for complex networks.” 2008. Web. 22 Aug 2019.

Vancouver:

Young SJ. Random dot product graphs: a flexible model for complex networks. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/26548.

Council of Science Editors:

Young SJ. Random dot product graphs: a flexible model for complex networks. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/26548


Georgia Tech

21. Wang, Ni. Statistical Learning in Logistics and Manufacturing Systems.

Degree: PhD, Industrial and Systems Engineering, 2006, Georgia Tech

 This thesis focuses on the developing of statistical methodology in reliability and quality engineering, and to assist the decision-makings at enterprise level, process level, and… (more)

Subjects/Keywords: Spatial prediction; Continuous approximation; Logistics systems; Reliability (Engineering) Mathematical models; Spatial analysis (Statistics); Approximation theory; Decision support systems

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APA (6th Edition):

Wang, N. (2006). Statistical Learning in Logistics and Manufacturing Systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/11457

Chicago Manual of Style (16th Edition):

Wang, Ni. “Statistical Learning in Logistics and Manufacturing Systems.” 2006. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/11457.

MLA Handbook (7th Edition):

Wang, Ni. “Statistical Learning in Logistics and Manufacturing Systems.” 2006. Web. 22 Aug 2019.

Vancouver:

Wang N. Statistical Learning in Logistics and Manufacturing Systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2006. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/11457.

Council of Science Editors:

Wang N. Statistical Learning in Logistics and Manufacturing Systems. [Doctoral Dissertation]. Georgia Tech; 2006. Available from: http://hdl.handle.net/1853/11457


Georgia Tech

22. Carroll, Charles W. An operations research approach to the economic optimization of a kraft pulping process.

Degree: PhD, Institute of Paper Science and Technology, 1959, Georgia Tech

Subjects/Keywords: Kraft pulping process; Operations research; Kinetics; Economic balance; Optimization; Statistics; Response surface technique; Mathematical models

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APA (6th Edition):

Carroll, C. W. (1959). An operations research approach to the economic optimization of a kraft pulping process. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/5853

Chicago Manual of Style (16th Edition):

Carroll, Charles W. “An operations research approach to the economic optimization of a kraft pulping process.” 1959. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/5853.

MLA Handbook (7th Edition):

Carroll, Charles W. “An operations research approach to the economic optimization of a kraft pulping process.” 1959. Web. 22 Aug 2019.

Vancouver:

Carroll CW. An operations research approach to the economic optimization of a kraft pulping process. [Internet] [Doctoral dissertation]. Georgia Tech; 1959. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/5853.

Council of Science Editors:

Carroll CW. An operations research approach to the economic optimization of a kraft pulping process. [Doctoral Dissertation]. Georgia Tech; 1959. Available from: http://hdl.handle.net/1853/5853

23. Dufresne, Stephane. A hierarchical modeling methodology for the definition and selection of requirements.

Degree: PhD, Aerospace Engineering, 2008, Georgia Tech

 This dissertation describes the development of a requirements analysis methodology that takes into account the concept of operations and the hierarchical decomposition of aerospace systems.… (more)

Subjects/Keywords: Requirements traceability; Unmanned aerial vehicle; Requirements analysis; Analytic network process; Requirements engineering; Decision making Mathematical models; Multilevel models (Statistics); Drone aircraft

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APA (6th Edition):

Dufresne, S. (2008). A hierarchical modeling methodology for the definition and selection of requirements. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/24755

Chicago Manual of Style (16th Edition):

Dufresne, Stephane. “A hierarchical modeling methodology for the definition and selection of requirements.” 2008. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/24755.

MLA Handbook (7th Edition):

Dufresne, Stephane. “A hierarchical modeling methodology for the definition and selection of requirements.” 2008. Web. 22 Aug 2019.

Vancouver:

Dufresne S. A hierarchical modeling methodology for the definition and selection of requirements. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/24755.

Council of Science Editors:

Dufresne S. A hierarchical modeling methodology for the definition and selection of requirements. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/24755


Georgia Tech

24. Moeller, Todd Keith. Conley-Morse Chain Maps.

Degree: PhD, Mathematics, 2005, Georgia Tech

 We introduce a new class of Conley-Morse chain maps for the purpose of comparing the qualitative structure of flows across multiple scales. Conley index theory… (more)

Subjects/Keywords: Conley index; Morse theory; Data analysis; Mathematical statistics; Morse theory; Algebraic topology; Homology theory

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APA (6th Edition):

Moeller, T. K. (2005). Conley-Morse Chain Maps. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/7221

Chicago Manual of Style (16th Edition):

Moeller, Todd Keith. “Conley-Morse Chain Maps.” 2005. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/7221.

MLA Handbook (7th Edition):

Moeller, Todd Keith. “Conley-Morse Chain Maps.” 2005. Web. 22 Aug 2019.

Vancouver:

Moeller TK. Conley-Morse Chain Maps. [Internet] [Doctoral dissertation]. Georgia Tech; 2005. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/7221.

Council of Science Editors:

Moeller TK. Conley-Morse Chain Maps. [Doctoral Dissertation]. Georgia Tech; 2005. Available from: http://hdl.handle.net/1853/7221


Georgia Tech

25. Prudius, Andrei A. Adaptive Random Search Methods for Simulation Optimization.

Degree: PhD, Industrial and Systems Engineering, 2007, Georgia Tech

 This thesis is concerned with identifying the best decision among a set of possible decisions in the presence of uncertainty. We are primarily interested in… (more)

Subjects/Keywords: Averaging for function estimation; Discrete and continuous stochastic optimization; Adaptive random search; Local search; Simulated annealing; Almost sure convergence; Simulation methods; Uncertainty; Decision making; Mathematical optimization

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APA (6th Edition):

Prudius, A. A. (2007). Adaptive Random Search Methods for Simulation Optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/16318

Chicago Manual of Style (16th Edition):

Prudius, Andrei A. “Adaptive Random Search Methods for Simulation Optimization.” 2007. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/16318.

MLA Handbook (7th Edition):

Prudius, Andrei A. “Adaptive Random Search Methods for Simulation Optimization.” 2007. Web. 22 Aug 2019.

Vancouver:

Prudius AA. Adaptive Random Search Methods for Simulation Optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2007. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/16318.

Council of Science Editors:

Prudius AA. Adaptive Random Search Methods for Simulation Optimization. [Doctoral Dissertation]. Georgia Tech; 2007. Available from: http://hdl.handle.net/1853/16318


Georgia Tech

26. Asif, Muhammad Salman. Primal dual pursuit: a homotopy based algorithm for the Dantzig selector.

Degree: MS, Electrical and Computer Engineering, 2008, Georgia Tech

 Consider the following system model y = Ax + e, where x is n-dimensional sparse signal, y is the measurement vector in a much lower… (more)

Subjects/Keywords: Statistical estimation; Random matrices; Convex optimization; Compressed sensing; Sparse signal recovery; Linear programming; LASSO; Model selection; L1 minimization; Dantzig shrinkability; Mathematical optimization; Homotopy theory; Signal processing

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APA (6th Edition):

Asif, M. S. (2008). Primal dual pursuit: a homotopy based algorithm for the Dantzig selector. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/24693

Chicago Manual of Style (16th Edition):

Asif, Muhammad Salman. “Primal dual pursuit: a homotopy based algorithm for the Dantzig selector.” 2008. Masters Thesis, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/24693.

MLA Handbook (7th Edition):

Asif, Muhammad Salman. “Primal dual pursuit: a homotopy based algorithm for the Dantzig selector.” 2008. Web. 22 Aug 2019.

Vancouver:

Asif MS. Primal dual pursuit: a homotopy based algorithm for the Dantzig selector. [Internet] [Masters thesis]. Georgia Tech; 2008. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/24693.

Council of Science Editors:

Asif MS. Primal dual pursuit: a homotopy based algorithm for the Dantzig selector. [Masters Thesis]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/24693

27. Dadush, Daniel Nicolas. Integer programming, lattice algorithms, and deterministic volume estimation.

Degree: PhD, Industrial and Systems Engineering, 2012, Georgia Tech

 The main subject of this thesis is the development of new geometric tools and techniques for solving classic problems within the geometry of numbers and… (more)

Subjects/Keywords: Integer programming; Lattice algorithms; Convex geometry; Volume estimation; Integer programming; Convex geometry; Polytopes; Ellipsoid; Mathematical optimization; Algorithms

…78 IV THE M-ELLIPSOID AND VOLUME ESTIMATION . . . . . . . 80 3.4 4.1 Introduction… …estimation (inertial ellipsoids). Here we consider the construction of an ellipsoid with… …an application to near-optimal deterministic volume estimation in the oracle model… …In Kannan’s view, this subject, which combined the classic mathematical theory of Minkowski… …covering, for which we give applications to volume estimation, lattice algorithms, and integer… 

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APA (6th Edition):

Dadush, D. N. (2012). Integer programming, lattice algorithms, and deterministic volume estimation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44807

Chicago Manual of Style (16th Edition):

Dadush, Daniel Nicolas. “Integer programming, lattice algorithms, and deterministic volume estimation.” 2012. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/44807.

MLA Handbook (7th Edition):

Dadush, Daniel Nicolas. “Integer programming, lattice algorithms, and deterministic volume estimation.” 2012. Web. 22 Aug 2019.

Vancouver:

Dadush DN. Integer programming, lattice algorithms, and deterministic volume estimation. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/44807.

Council of Science Editors:

Dadush DN. Integer programming, lattice algorithms, and deterministic volume estimation. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44807


Georgia Tech

28. Reynolds, Sue Bath. Statistical estimation and changepoint detection methods in public health surveillance.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

 This thesis focuses on assessing and improving statistical methods implemented in two areas of public health research. The first topic involves estimation of national influenza-associated… (more)

Subjects/Keywords: Statistical estimation; Changepoint detection

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APA (6th Edition):

Reynolds, S. B. (2015). Statistical estimation and changepoint detection methods in public health surveillance. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54906

Chicago Manual of Style (16th Edition):

Reynolds, Sue Bath. “Statistical estimation and changepoint detection methods in public health surveillance.” 2015. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/54906.

MLA Handbook (7th Edition):

Reynolds, Sue Bath. “Statistical estimation and changepoint detection methods in public health surveillance.” 2015. Web. 22 Aug 2019.

Vancouver:

Reynolds SB. Statistical estimation and changepoint detection methods in public health surveillance. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/54906.

Council of Science Editors:

Reynolds SB. Statistical estimation and changepoint detection methods in public health surveillance. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54906


Georgia Tech

29. Tan, Zhenyu. Dynamic state estimation based transmission line protection.

Degree: PhD, Electrical and Computer Engineering, 2016, Georgia Tech

 This thesis proposed a dynamic state estimation based protection algorithm for the transmission line to 1) eliminate complex protection settings in order to prevent human… (more)

Subjects/Keywords: Dynamic state estimation; Protective relay

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APA (6th Edition):

Tan, Z. (2016). Dynamic state estimation based transmission line protection. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56306

Chicago Manual of Style (16th Edition):

Tan, Zhenyu. “Dynamic state estimation based transmission line protection.” 2016. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/56306.

MLA Handbook (7th Edition):

Tan, Zhenyu. “Dynamic state estimation based transmission line protection.” 2016. Web. 22 Aug 2019.

Vancouver:

Tan Z. Dynamic state estimation based transmission line protection. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/56306.

Council of Science Editors:

Tan Z. Dynamic state estimation based transmission line protection. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56306


Georgia Tech

30. Moore, Michael George. Maximum likelihood estimation of Poisson and Hawkes processes and extensions to Hawkes process analysis.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 The purpose of this work is to improve our ability to extract information from data generated by Poisson and Hawkes processes. Our principal focus is… (more)

Subjects/Keywords: Poisson; Hawkes; Point process; Estimation

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APA (6th Edition):

Moore, M. G. (2018). Maximum likelihood estimation of Poisson and Hawkes processes and extensions to Hawkes process analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60727

Chicago Manual of Style (16th Edition):

Moore, Michael George. “Maximum likelihood estimation of Poisson and Hawkes processes and extensions to Hawkes process analysis.” 2018. Doctoral Dissertation, Georgia Tech. Accessed August 22, 2019. http://hdl.handle.net/1853/60727.

MLA Handbook (7th Edition):

Moore, Michael George. “Maximum likelihood estimation of Poisson and Hawkes processes and extensions to Hawkes process analysis.” 2018. Web. 22 Aug 2019.

Vancouver:

Moore MG. Maximum likelihood estimation of Poisson and Hawkes processes and extensions to Hawkes process analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/1853/60727.

Council of Science Editors:

Moore MG. Maximum likelihood estimation of Poisson and Hawkes processes and extensions to Hawkes process analysis. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60727

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